The present invention relates to a process for underwriting insurance applications, and more particularly to a process for optimizing decisions for underwriting insurance applications based on flexible fuzzy rule-based and case-based systems.
A trained individual or individuals traditionally perform insurance underwriting. A given application for insurance (also referred to as an “insurance application”) may be compared against a plurality of underwriting standards set by an insurance company. The insurance application may be classified into one of a plurality of risk categories available for a type of insurance coverage requested by an applicant. The risk categories then affect a premium paid by the applicant, e.g., the higher the risk category, the higher the premium. A decision to accept or reject the application for insurance may also be part of this risk classification, as risks above a certain tolerance level set by the insurance company may simply be rejected.
There can be a large amount of variability in the insurance underwriting process when performed by individual underwriters. Typically, underwriting standards cannot cover all possible cases and variations of an application for insurance. The underwriting standards may even be self-contradictory or ambiguous, leading to uncertain application of the standards. The subjective judgment of the underwriter will almost always play a role in the process. Variation in factors such as underwriter training and experience, and a multitude of other effects can cause different underwriters to issue different, inconsistent decisions. Sometimes these decisions can be in disagreement with the established underwriting standards of the insurance company, while sometimes they can fall into a “gray area” not explicitly covered by the underwriting standards.
Further, there may be an occasion in which an underwriter's decision could still be considered correct, even if it disagrees with the written underwriting standards. This situation can be caused when the underwriter uses his/her own experience to determine whether the underwriting standards may or should be interpreted and/or adjusted. Different underwriters may make different determinations about when these adjustments are allowed, as they might apply stricter or more liberal interpretations of the underwriting standards. Thus, the judgment of experienced underwriters may be in conflict with the desire to consistently apply the underwriting standards.
Most of the key information required for automated insurance underwriting is structured and standardized. However, some sources of information may be non-standard or not amenable to standardization. By way of example, an attending physician statement (“APS”) may be almost as unique as each individual physician. However, a significant fraction of applications may require the use of one or more APS due to the presence of medical impairments, age of applicants, or other factors. Without such key information, the application underwriting process cannot be automated for these cases.
Conventional methods for dealing with some of the problems described above have included having human underwriters directly reading the APS. However, an APS document can be as long as several tens of pages. Therefore, the manual reading process, combined with note-taking and consulting other information, such as an underwriting manual or the like, can greatly extend the cycle-time for each application processed, increase underwriter variability, and limit capacity by preventing the automation of the decision process.
Other drawbacks may also exist.